langchain.retrievers.zilliz.ZillizRetriever

class langchain.retrievers.zilliz.ZillizRetriever(*, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, embedding_function: Embeddings, collection_name: str = 'LangChainCollection', connection_args: Optional[Dict[str, Any]] = None, consistency_level: str = 'Session', search_params: Optional[dict] = None, store: Zilliz, retriever: BaseRetriever)

Bases: BaseRetriever

Retriever for the Zilliz API.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

param collection_name: str = 'LangChainCollection'

The name of the collection in Zilliz.

param connection_args: Optional[Dict[str, Any]] = None

The connection arguments for the Zilliz client.

param consistency_level: str = 'Session'

The consistency level for the Zilliz client.

param embedding_function: langchain.embeddings.base.Embeddings [Required]

The underlying embedding function from which documents will be retrieved.

param metadata: Optional[Dict[str, Any]] = None

Optional metadata associated with the retriever. Defaults to None This metadata will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks. You can use these to eg identify a specific instance of a retriever with its use case.

param retriever: langchain.schema.retriever.BaseRetriever [Required]

The underlying retriever.

param search_params: Optional[dict] = None

The search parameters for the Zilliz client.

param store: langchain.vectorstores.zilliz.Zilliz [Required]

The underlying Zilliz store.

param tags: Optional[List[str]] = None

Optional list of tags associated with the retriever. Defaults to None These tags will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks. You can use these to eg identify a specific instance of a retriever with its use case.

add_texts(texts: List[str], metadatas: Optional[List[dict]] = None) → None

Add text to the Zilliz store

Parameters

• texts (List[str]) – The text

• metadatas (List[dict]) – Metadata dicts, must line up with existing store

async aget_relevant_documents(query: str, *, callbacks: Callbacks = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → List[Document]

Asynchronously get documents relevant to a query. :param query: string to find relevant documents for :param callbacks: Callback manager or list of callbacks :param tags: Optional list of tags associated with the retriever. Defaults to None

These tags will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks.

Parameters

metadata – Optional metadata associated with the retriever. Defaults to None This metadata will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks.

Returns

List of relevant documents

async ainvoke(input: str, config: Optional[RunnableConfig] = None) → List[Document]

validator create_client  »  all fields

get_relevant_documents(query: str, *, callbacks: Callbacks = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → List[Document]

Retrieve documents relevant to a query. :param query: string to find relevant documents for :param callbacks: Callback manager or list of callbacks :param tags: Optional list of tags associated with the retriever. Defaults to None

These tags will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks.

Parameters

metadata – Optional metadata associated with the retriever. Defaults to None This metadata will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks.

Returns

List of relevant documents

invoke(input: str, config: Optional[RunnableConfig] = None) → List[Document]

to_json() → Union[SerializedConstructor, SerializedNotImplemented]

to_json_not_implemented() → SerializedNotImplemented

property lc_attributes: Dict

Return a list of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor.

property lc_namespace: List[str]

Return the namespace of the langchain object. eg. [“langchain”, “llms”, “openai”]

property lc_secrets: Dict[str, str]

Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_KEY”}

property lc_serializable: bool

Return whether or not the class is serializable.

model Config

Bases: object

Configuration for this pydantic object.

arbitrary_types_allowed = True